1. Field of the Invention
The present invention relates to a system and method for improving the contrast in ultrasound images. In particular, the present invention relates to a technique for significantly improving contrast resolution in ultrasound images by compressing the spectrum amplitude while maintaining adequate signal to noise ratio.
2. Description of the Prior Art
Ultrasonic wavefront distortion which includes phase aberration and waveform distortion develops as coherent ultrasonic waves propagate through an inhomogeneous medium, such as the breast. Wavefront distortion sources inside the breast can be modeled as incoherent scattering and coherent multipath interference. Scattering reduces the target strength, broadens the image lobe, raises the background level, and therefore lowers the image contrast. Multipath interference produces ghost image artifacts or false targets in addition to true targets in the image. As known by those skilled in the ultrasound art, the interference problem is more severe when the aperture is large for high spatial resolution because the transducers cover large volumes of inhomogeneous tissue and the ultrasonic beams interact with more spatial variations in tissue composition.
FIG. 1 illustrates the effects of incoherent scattering and multipath interference upon a point source image or its angular spectrum (intensity distribution), where FIG. 1(a) illustrates scattering induced distortion in the angular source intensity distribution and FIG. 1(b) illustrates refraction and scattering induced distortion in the angular source intensity distribution. Without medium induced distortion, a diffraction limited coherent spectrum is produced. However, with the presence of medium induced scattering, the overall angular spectrum is the sum of coherent and scattered spectra, as shown in FIG. 1(a). Because of scattering the spectrum is broadened and reduced in strength. The background level is increased and, therefore, image contrast is reduced. In general, the scattered energy increases with the propagation depth. On the other hand, with the presence of both medium induced scattering and coherent multipath interference, the angular spectrum is the superposition of the coherent lobe, coherent interference lobes and the scattering spectrum, as shown in FIG. 1(b). In FIG. 1(b), the interference lobes, produced by bending and splitting of coherent waves as well as interference of coherent waves with multipath waves caused by refraction and reflection, appear as false targets.
Generally, the refraction and scattering induced wavefront distortion consists of phase and waveform distortions. Most conventional algorithms compensate the phase distortion but do not address the waveform distortion. For example, two basic phase deaberration algorithms have been proposed by Flax et al. in an article entitled "Phase Aberration Correction Using Signals From Point Reflectors and Diffuse Scatterers: Basic Principles," IEEE Trans. Ultrason. Ferroelec. Freq. Cont., Vol. 35, No. 6, pages 758-767 (November 1988) and by Nock et al. in an article entitled "Phase Aberration Correction in Medical Ultrasound Using Speckle Brightness as a Quality Factor," J. Acoust. Soc. Am., Vol. 85, No. 5, pages 1819-1833 (1989). These algorithms adjust time delays of received waveforms at different elements of a phased array to compensate delay errors due to an inhomogeneous medium and consequently reduce the scattered energy. Although these two algorithms have been derived from different optimization criteria, their performances are similar; they minimize time delay errors or phase errors but leave waveform distortion intact.
Generally, when certain correlation properties exist in the wavefront, such phase deaberration algorithms are useful to partially remove phase distortion and build up the strength of the coherent field. However, waveform distortion remains, as does residual phase distortion, and produces a significantly high background level in the spectrum. As a result, such basic deaberration algorithms are suitable only for weak scattering that can be modeled as a thin random phase screen located in the plane of the receiving aperture.
FIG. 2 schematically shows the effects of phase deaberration, where FIGS. 2(a) and 2(b) respectively illustrate the angular source intensity distributions of FIGS. 1(a) and 1(b) after phase compensation.
Several other techniques are known in the art for compensating phase distortion. With reference to FIG. 3, several such distortion correction methods will now be compared in connection with the correction of a complex spectrum amplitude of a point source image measured in array f=Aexp(j.phi.). Those skilled in the art will appreciate that most of these techniques, as well as the technique of the invention, are not limited to point source targets and are applicable to diffuse scattering mediums such as the breast.
Consider complex signal vectors S.sub.0 (x)=A.sub.0 exp(j.PSI..sub.0) and S(x)==Aexp(j.PSI.) received at an ultrasound array in the absence and presence of distortion, respectively. S.sub.0 and S are functions of position in the array which is identified by element number. The multiplicative distortion vector f=S/S.sub.0 =aexp(j.phi.) is the ratio of S to S.sub.0, where a=A/A.sub.0. FIG. 3 compares deaberration transformations for a complex sample f, which is the distortion vector for an instantaneous sample of the radiation field. Transformations to the real axis X all correct phase. Those transformations to the left on the real axis X maximize signal-to-noise ratio but increase amplitude distortion, while those transformations to the right maximize imaging fidelity but increase noise. Thus, the optimum compensation weight vector or transformation is the right-most one (Inverse Filtering (IF) w=a.sup.-1 exp(-j.phi.)) which carries the distortion component of the complex sample to the intersection of the X axis and the unit circle, for then both amplitude and phase are exactly corrected. On the other hand, as illustrated in FIG. 3, the left-most transformation is matched filtering (MF) (w=aexp(-j.phi.), which squares the amplitude and conjugates the phase.
MF is theoretically optimum for maximizing signal-to-noise ratio on a white, Gaussian channel. MF is an optimum solution for detection (radar) but not so when fidelity is an important criterion, as in medical imaging. However, MF does satisfy the requirement for phase correction. Examples of MF algorithms are the Dominant Scatterer Algorithm (DSA) described by Steinberg in an article entitled "Radar Imaging From a Distorted Array: The Radio Camera Algorithm and Experiments," IEEE Trans. Antennas Propag., Vol. AP-29, No. 5, pages 740-748 (September 1981), and the Time Reversal Mirror (TRM) described by Fink in an article entitled "Time Reversal of Ultrasonic Fields--Part I: Basic Principles," IEEE Trans. Ultrason. Ferroelec. Freq. Contr., Vol. 39, pages 555-566 (1992). MF algorithms are useful when wavefront distortion resides principally in phase, with amplitude relatively unaffected. Otherwise, MF algorithms would be less effective than if amplitude were ignored and phase only were corrected, for by squaring the wavefront amplitude, the MF algorithms increase amplitude variance which contributes to the increase of energy in the sidelobe region. This is problematic when substantial wavefront distortion is present.
Now consider what happens when a phantom consisting of a random phase screen is placed at a receiving transducer. The element signal samples are correct in amplitude and distorted only in phase by a random additive component. Phase aberration correction, consisting of phase conjugation (PC), is then the optimum compensation. The signal amplitude is unchanged and phase error is completely compensated by conjugation. As shown in FIG. 3, PC is represented by the second transformation from the left. Time delay compensation (TDC) is in the same class of transformations.
IF is theoretically ideal for fidelity but has drawbacks. In particular, because the IF adjusts the channel gain to be the reciprocal of the signal strength, at points in the receiving aperture where signal strength is weak the enhanced channel gain raises the noise to the point where signal-to-noise ratio can be impaired. This is particularly troublesome when there is coherent refractive interference in the receiving array. A second potential problem is that an IF is unstable when the distorting medium has zeroes in the complex plane. Thus, the right-most transformation carries the wavefront correction too far. The compensation of wavefront distortion, on the other hand, presents a more difficult problem because there is no general way to reduce wavefront amplitude distortion.
Liu et al. disclose in an article entitled "Correction of Ultrasonic Wavefront Distortion Using Backpropagation and Reference Waveform Method for Time-Shift Compensation," J. Acoust. Soc. Am., Vol. 96, pages 649-660 (1994), a backpropagation technique (BPT) for improving the time-delay type compensation algorithm by backpropagating the received waveforms to an optimal distance and then performing time-delay compensation at this distance. The backpropagation provides first order correction of wavefront amplitude distortion due to propagation from the backpropagation distance to the receiving aperture and, therefore, performs better than phase deabberation at the aperture. BPT does not employ any amplitude weighting, and the BPT transformation is somewhere to the right of TDC and PC in FIG. 3.
On the other hand, Carpenter et al. describe in an article entitled "Correction of Distortion in US Images Caused By Subcutaneous Tissues: Results in Tissue Phantoms and Human Subjects," Radiology, Vol. 195, pages 563-567 (1995) a model-based approach that uses a priori information of the speeds of the rectus muscle layers inside the abdominal wall has been developed to correct double image artifacts caused by refraction when imaging the abdomen. However, such a technique is not practical for general clinical settings since the model-based approach requires prior information about the source of the distortion. A wavefront distortion correction technique is desired that does not require such prior information about the source of the distortion.
The complex amplitude weights of MF, PC, and IF are, respectively, a, 1, and a.sup.-1, each multiplied by (exp(-j.phi.)). The signal after weighting is a.sup.2, a, and 1, respectively. The first and last weights are far from optimum for the reasons noted above. An intermediate transformation is desired which is a compromise between these weightings and which does not require prior information about the source of the distortion. Ideally, the signal after weighting has an amplitude approaching 1 and approaches the amplitude and phase correction results of IF yet does not decrease the signal to noise ratio and cause the transformation to become unstable as in the IF transformation. The present invention has been designed for this purpose by combining a spectrum amplitude compression operation with phase deaberration.